Automatic ceramic identification using machine learning. Lusitanian amphorae and Faience. Two Portuguese case studies

Automatic ceramic identification using machine learning. Lusitanian amphorae and Faience. Two Portuguese case studies

This article presents a novel approach to classifying archaeological artefacts using machine learning, specifically deep learning, rather than relying on traditional, time-consuming human-based methods. By employing Convolutional Neural Networks (CNNs), this approach aims to expedite and enhance the...

Full description

Saved in:
Bibliographic Details
Main Authors: Joel Santos, Diogo A.P. Nunes, Ruslan Padnevych, José Carlos Quaresma, Martim Lopes, Joana Gil, João Pedro Bernardes, Tania Manuel Casimiro
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:Science and Technology of Archaeological Research
Subjects:
Deep learning
machine learning
artificial intelligence
Amphorae
Faience
ceramic identification
Online Access:https://www.tandfonline.com/doi/10.1080/20548923.2024.2343214
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.tandfonline.com/doi/10.1080/20548923.2024.2343214

Similar Items